#13 Vault (9-8)

avg: 2004.36  •  sd: 47.88  •  top 16/20: 91.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
7 DiG Win 12-11 2292.51 Jul 15th TCT Pro Elite Challenge East 2023
19 Sub Zero Win 15-9 2381.06 Jul 15th TCT Pro Elite Challenge East 2023
38 Phantom Win 15-12 1925.47 Jul 15th TCT Pro Elite Challenge East 2023
6 Ring of Fire Loss 10-11 2055.66 Jul 16th TCT Pro Elite Challenge East 2023
12 Raleigh-Durham United Win 14-12 2227.58 Jul 16th TCT Pro Elite Challenge East 2023
39 Pittsburgh Temper Win 12-8 2065.87 Aug 19th TCT Elite Select Challenge 2023
26 Sprout Win 12-11 1870.77 Aug 19th TCT Elite Select Challenge 2023
27 Omen Win 15-10 2193.39 Aug 19th TCT Elite Select Challenge 2023
19 Sub Zero Loss 12-13 1740.58 Aug 20th TCT Elite Select Challenge 2023
20 Zyzzyva Win 14-11 2173.55 Aug 20th TCT Elite Select Challenge 2023
14 Sockeye Win 12-11 2124.88 Aug 20th TCT Elite Select Challenge 2023
3 Revolver Loss 6-15 1645.3 Sep 2nd TCT Pro Championships 2023
4 Chain Lightning Loss 12-15 1911.4 Sep 2nd TCT Pro Championships 2023
8 Johnny Bravo Loss 13-15 1898.6 Sep 2nd TCT Pro Championships 2023
6 Ring of Fire Loss 12-14 1959.7 Sep 3rd TCT Pro Championships 2023
2 PoNY Loss 11-13 2105.1 Sep 3rd TCT Pro Championships 2023
10 Rhino Slam! Loss 12-15 1785.31 Sep 4th TCT Pro Championships 2023
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
What's the algorithm again?
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
Is there a longer explanation of all this?
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)